首页> 外国专利> Method and apparatus of recognizing facial expression base on multi-modal

Method and apparatus of recognizing facial expression base on multi-modal

机译:基于多模态的面部表情识别方法及装置

摘要

Constructing a CNN model expression database through learning using the CNN model; Constructing an SVM model expression database through learning using the SVM model; Obtaining facial expression data using the CNN model for the recognition image; Acquiring facial expression data using an SVM model for a recognition image; The CNN model facial expression database is searched for the facial expression data using the CNN model to extract the closest CNN model facial expression classification data, and the first weight is added to the extracted CNN model facial expression classification data to obtain CNN model weight operation expression data Calculating; The SVM model facial expression database is searched for the facial expression data using the SVM model to extract the closest SVM model facial expression classification data value and the second weight is added to the extracted SVM model facial expression classification data to obtain the SVM model weight operation facial expression data value ; A facial recognition step of combining the CNN model weighting operation facial expression data and the SVM model weighting facial expression data to calculate final facial expression data and selecting a most probable value to recognize facial expression; The method comprising the steps of:
机译:通过使用CNN模型的学习来构建CNN模型表达数据库;通过学习使用SVM模型来构建SVM模型表达数据库;使用CNN模型获取识别图像的面部表情数据;使用SVM模型获取面部表情数据以识别图像;使用CNN模型在CNN模型面部表情数据库中搜索面部表情数据,以提取最接近的CNN模型面部表情分类数据,并将第一权重添加到所提取的CNN模型面部表情分类数据中以获得CNN模型体重运算表达式数据计算;使用SVM模型在SVM模型面部表情数据库中搜索面部表情数据,以提取最接近的SVM模型面部表情分类数据值,并将第二权重添加到所提取的SVM模型面部表情分类数据中以获得SVM模型权重运算面部表情数据值;脸部识别步骤,将CNN模型加权操作脸部表情数据和SVM模型加权脸部表情数据相结合,计算出最终的脸部表情数据,并选择最可能的值来识别脸部表情;该方法包括以下步骤:

著录项

  • 公开/公告号KR101893554B1

    专利类型

  • 公开/公告日2018-08-30

    原文格式PDF

  • 申请/专利权人 영남대학교 산학협력단;

    申请/专利号KR20170019996

  • 发明设计人 이찬수;김민현;김진철;

    申请日2017-02-14

  • 分类号G06T7/33;G06F17/30;G06K9;G06N3/08;

  • 国家 KR

  • 入库时间 2022-08-21 12:37:11

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号